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Every drug given to a patient must reach its site of action in therapeutic concentrations, and similarly, molecular imaging agents need to

reach their target so they can bind or react to generate contrast. At the core of this problem is multiscale transport, from the macroscopic whole animal/person and organ level to the tissue, cellular, and subcellular distribution. This distribution is driven by kinetic rates determined by the local physiology (often out of the molecular engineer’s control) and the drug physicochemical/structural properties. By applying predictive computational simulations of transport, classic chemical engineering principles emerge from many pressing problems faced in drug d development and imaging agent design. In this presentation, we will cover three specific examples. First, we’ll analyze targeted therapeutics in cancer, where reaction-diffusion analysis explains some counter-intuitive results where less potency can result in higher tumor killing (which needs to be incorporated in drug development). Second, we’ll discuss imaging agent design for Type 1 diabetes, where off-target expression has stymied the development of an imaging agent for early diagnosis. We’ll present an imaging strategy using kinetic control of delivery rather than thermodynamic (binding) control that shows promising results for generating specific targeting. Finally, we’ll demonstrate how multi-scale

modeling can help design orally delivered near-infrared fluorescent imaging agents for needle-free and radiation-free screening of breast cancer and rheumatoid arthritis. This approach highlights the capability of molecular imaging to overcome the poor specificity of mammography (resulting in billions of wasted dollars in over-diagnosis) and the potential for curing rheumatoid arthritis.